WIN BIG WITH GOOGLE CLOUD

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1 WIN BIG WITH GOOGLE CLOUD

2 HYPER PERSONALIZATION AND AD TARGETING Predict ad to be displayed based on users past behavior, demographics and seasonality Lost revenue due to customers abandoning shopping carts Unable to rapidly introduce new ads or coupons based on current promotions Rigid infrastructure which makes it difficult to change and deploy enhancements to existing algorithms Drive sales through better audience engagement Improve customer satisfaction through personalized ads and coupons Provide consistent user experience across various channels - website, mobile, etc Retail, CPG, big box retailers CMO New product launch Revenue goals - insights to cross sell and up sell Pub/Sub 2

3 FRAUD AND ANOMALY DETECTION Identify outliers in credit card transactions and predict fraudulent ones Unable to identify and stop fraudulent credit card transactions in real time Fraudulent transactions lead to a variety of negative outcomes including loss of revenue, loss of customer confidence and decreased customer satisfaction Proactively deny fraudulent transactions and mitigate risk Improved customer satisfaction through real time notifications Financial services Money laundering and risk mitigation departments Payment processing, Real-time payment transaction Finance Team New data compliance and regulations Targeting new customer base Pub/Sub 3

4 FLEET PREVENTIVE MAINTENANCE Analyze IOT streaming data to predict machine failure and enable predictive maintenance Loss of business and customer satisfaction issues when deadlines are not met due to equipment failure Cost of maintenance that can be prevented Support for IOT sensor/mqtt integration to support extremely large datasets Reduced costs from equipment failure Improved end customer satisfaction by meeting customer expectations and deadlines Real-time data processing and prediction at scale Manufacturing, Distributors, 3rd party logistics Customer Service department Fleet Maintenance Customer satisfaction - Improve NPS Upgrade from legacy technology of preventive maintenance Pub/Sub Cloud IOT 4

5 VIDEO INTELLIGENCE Analyze video content and enrich it with keywords, face recognition, related videos, etc Users today expect an experience that s on par with the best video content providers online. They expect to search for content easily, find related videos or find more information on a video they are watching. Not providing such an experience will lead to lost subscribers. Provide better user experience that s on par with today s expectations around search and insights Ability to monetize video content by providing contextual insights for a viewer Reduce costs by automating creation of a highlights reel - something that an editor would have to do manually Media publishers, Broadcasters, Video content providers Marketing department Content team Customer satisfaction - improve user engagement Monetize video content Speech API Video Intelligence API 5

6 REAL TIME RETAIL ANALYTICS Real time inventory in warehouse given demand from POS or e-commerce Product shortfall leads to lost sales and reduced customer satisfaction High inventory in retail stores consumes valuable shelf space and incurs costs Rigid infrastructure makes it difficult to change and deploy enhancements to existing algorithms Get 360 degree view into inventory and orders Improve customer satisfaction by suggesting in real time when and where a particular product is available. Provide consistent user experience across various channels - website, mobile, etc. Retailers E-commerce teams Vendor/Supplier management teams Improve inventory forecasting Auto replenishment and changes to vendor managed inventory Pub/Sub 6

7 INTELLIGENT CASE ROUTING Faster and better customer service via automated responses with live agent intervention as necessary High case volume industries e.g Financial Services and Insurance Companies Support personnel spending time to understand and triage new support requests is time consuming and incurs costs Customers no longer are happy getting a canned auto response, they want quick resolution to their requests. The longer it takes to resolve support cases the lower the customer satisfaction. Support for global audience Rapid and accurate triage of customer support cases leads to better customer satisfaction Reduced time and costs in resolving support cases Allows support personnel to spend time on complex cases Customer Service department Improve NPS and customer satisfaction Increase customer support efficiency Dialogflow AppEngine Translate API 7

8 MEDICAL IMAGE CLASSIFICATION Medical image classification with improved accuracy and use of public cloud platform. e.g Image profiling. Legacy technology with client-server based tools Installation and maintenance to support various OS Long turnaround time to support new machine learning models Single platform for storage, analysis, machine learning and visualization Easy to add social collaboration and information sharing features Google cloud ML provides the scale to train models constantly and have accuracy rate Healthcare Bioinformatics team Technology development team Migration to cloud initiatives Support for new ML and data performance Vision API 8

9 DATAWAREHOUSE MIGRATION Migrate data from Redshift to Bigquery, includes schema conversion and comparing cost and query performance Infrastructure and storage costs and maintenance Limited support for features such as serverless architecture, partitions, federated data sources Complex ETL and integration layer Ability to setup a petabyte scale datawarehouse at a rapid pace and low cost Architecture and performance of allows simplification of end to end process by avoiding complex ETL and BigData jobs Scalable serverless infrastructure Applicable to all domains IT Directors Datawarehouse and bigdata teams Multi-cloud platform deployment New data analytics initiatives 9

10 HADOOP MIGRATION Migrate Spark projects to Dataproc e.g. job Applicable to all domains. High cost of DevOps maintenance ETL performance issues leads to delays in processing Separate development design for batch and streaming use cases End to end pipeline consolidation to a single scalable stack Access to Google ML APIs and integration with SparkML and TensorFlow models IT Directors Datawarehouse and Bigdata teams. Cost reduction in DevOps Consolidate to one platform for end to end pipeline. Pub/Sub Dataproc Datalab 10

11 AUTOMATED DOCUMENT EXTRACTION Automate information retrieval from documents leading to faster time to action Any industry that handles large number of documents e.g legal, insurance, financial Businesses receive hard copy documents via various channels and extracting data from them manually is time consuming and error prone. These delays can impact business performance or customer satisfaction. Automate data extraction from documents allowing your team to work on value added tasks. Avoid errors during data extraction to improve business performance and customer satisfaction. CIO CFO Reduced time to process documents Improve customer satisfaction Vision API AppEngine Cloud Storage 11

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